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Boffin vs Graphenium

Which one should you try?

Boffin

Free

Best for Teams using Cursor, Claude Code, or similar AI coding agents

Graphenium

Free

Best for Large or multi-module repositories

Pricing, capabilities and platforms side by side. Prices are as of the "Pricing checked" date in the table.

Boffin

Boffin

Boffin sits between your codebase and agents like Cursor, Claude Code, or Codex, feeding each edit the specific rules that apply to that file rather than a flat global prompt. The GitHub page describes it as a staff-engineer control layer: it enforces verification steps after code changes and routes constraints designed to protect existing test coverage and API contracts. It ships via npx boffinit, carries an MIT license, and has no hosted API or agent logic of its own — it controls agents, it does not become one. Where it shows limits: if your team needs dynamic rule generation or the constraint set grows complex enough to require its own maintenance cycle, you are now managing a rules system on top of your codebase. Teams that reach that ceiling tend to bake the constraints directly into their CI pipeline instead.

Graphenium

Graphenium

Graphenium indexes a repository into a persistent, queryable knowledge graph and exposes it over MCP, so assistants like Claude or Cursor can answer dependency and call-chain questions in roughly 20 ms without reading source files at each turn. The graph survives across sessions, which means structural knowledge does not have to be rebuilt every time you open a new conversation. The gain is sharpest on large or multi-module repos where grep-and-trace navigation collapses under its own weight. The constraint is real: this is a static graph service, not an agent — it answers questions but does not plan or act, so any reasoning on top of the data remains the assistant's job.

AttributeBoffinGraphenium
PricingFreeFree
Pricing checkedNot checked yetNot checked yet
Free trialNot statedNot stated
Open sourceYesYes
Has APINoYes
Self-hosted optionYesYes
PlatformsNode.js 18+, Cursor, Claude Code, Codex, OpenCodeCross-platform (Rust)
Pros
  • Per-file rule routing rather than a flat global prompt, which means a high-risk payment module gets strict architectural constraints while a utility file gets none — without you manually managing which agent sees what.
  • Post-edit verification hooks built into the control layer, so an agent cannot silently break a test or drift an API contract and move on before you catch it.
  • Plugin configs ship for Claude, Cursor, Windsurf, Codex, and Kiro, which means you are not rewriting integration logic when your team switches agents or runs more than one in parallel.
  • MIT license and npx install with no hosted API, so there is no vendor dependency, no data leaving your environment, and no cost gate between a proof-of-concept and a production deployment.
  • Self-hosted by design, which means your codebase and your rules stay on your infrastructure — a requirement for teams operating under data-residency or IP constraints that a SaaS control layer cannot satisfy.
  • Persistent graph survives session boundaries, so an assistant navigating a large repo does not waste token budget re-establishing structural context at the start of every conversation.
  • MCP-native interface means Claude, Cursor, and other compatible assistants query the graph without a custom integration layer — which avoids the glue-code maintenance burden that plagues one-off tool wrappers.
  • Approximately 20 ms query latency (per project documentation) on call-chain and dependency lookups, so structural questions do not introduce noticeable lag into assistant response cycles.
  • MIT-licensed and self-hosted, so the repository's source code never leaves your infrastructure — critical for teams whose codebases cannot touch external APIs under their security policy.
  • .grapheniumignore support lets teams exclude generated or vendored directories, keeping the graph lean and preventing noise from third-party code polluting dependency queries.
Cons
  • Rule files for each scoped path require active maintenance: when a module is restructured or renamed, the corresponding rules become stale and the agent receives either wrong guidance or nothing. There is no automated sync between your file tree and your rule definitions — that is a manual process, and on a codebase with frequent structural changes, it becomes a recurring coordination cost.
  • The tool has no mechanism for generating or updating rules from observed agent behavior; every constraint is hand-authored. Teams whose constraint sets grow beyond a few dozen scoped rules report the rules directory becoming its own engineering artifact — at which point some abandon the layer and encode the same constraints as linter plugins and test fixtures that run in CI regardless of which agent triggered the change.
  • There is no API, so any tooling that needs to query or update rules programmatically — a dashboard, a rule-review workflow, an audit log — requires building directly against the file system. Teams that need visibility into which rules fired on which edits have no built-in observability and must instrument this themselves.
  • Re-indexing is a manual step: the graph does not update automatically when files change, so after a significant refactor or merge, dependency answers will be stale until someone runs the indexer again — teams doing rapid iteration find themselves managing index freshness as a separate chore.
  • The project shows 1 commit and 8 stars at the time of scraping, which means community-validated workarounds, issue resolutions, and third-party integrations are sparse; teams hitting an edge case will be debugging against thin documentation and a small issue backlog rather than a searchable community history.
  • There is no hosted or managed option — setup, updates, and uptime are entirely the team's responsibility; teams without the infrastructure bandwidth to run a self-hosted Rust service will switch to a managed code-intelligence alternative rather than absorb the operational overhead.

Made up your mind?

Boffin

Free

Best for Teams using Cursor, Claude Code, or similar AI coding agents

Graphenium

Free

Best for Large or multi-module repositories

Specs come from each tool's own site and docs (how we test). AIDiveForge is editorially independent.